The arange()
method creates an array with evenly spaced elements as per the interval.
Example
import numpy as np
# create an array with elements from 5 to 10
array1 = np.arange(5, 10)
print(array1)
# Output: [5 6 7 8 9]
arange() Syntax
The syntax of arange()
is:
numpy.arange(start = 0, stop, step = 1, dtype = None)
arange() Argument
The arange()
method takes the following arguments:
start
(optional)- the start value of the interval range (int
orreal
)stop
- the end value of the interval range (exclusive) (int
orreal
)step
(optional)- step size of the interval (int
orreal
)dtype
(optional)- type of output array(dtype
)
Notes:
step
can't be zero. Otherwise, you'll get aZeroDivisionError
.- If
dtype
is omitted,arange()
will determine the type of the array elements from the types of other parameters. - In
arange()
, thestop
value is exclusive.
arange() Return Value
The arange()
method returns an array of evenly spaced values.
Example 1: Create a 1-D Array Using arange
import numpy as np
# create an array with first five elements
array1 = np.arange(5)
# create an array with elements from 5 to 10(exclusive)
array2 = np.arange(5, 10)
# create an array with elements from 5 to 15 with stepsize 2
array3 = np.arange(5, 15, 2)
print(array1)
print(array2)
print(array3)
Output
[0 1 2 3 4] [5 6 7 8 9] [ 5 7 9 11 13]
Note:
If only one argument is passed, it represents the stop
value with start = 0
and step = 1
.
If two arguments are passed, they represent the start
and the stop
values with step = 1
.
Example 2: Create a Floating Point 1-D Array Using arange
import numpy as np
# create an array with elements from 0 to 1 with stepsize 0.2
array1 = np.arange(0, 1, 0.2)
print(array1)
Output
[0. 0.2 0.4 0.6 0.8]
Example 3: Passing Negative Valued Arguments in arange
import numpy as np
# create an array with elements from -5 to 5 with step size 2
array1 = np.arange(-5, 5, 2)
# create an array with elements from -15 to -5 with step size 2
array2 = np.arange(-15, -5, 2)
# create an array with elements from 15 to 5 with step size -2
array3 = np.arange(15, 5, -2)
print(array1)
print(array2)
print(array3)
Output
[-5 -3 -1 1 3] [-15 -13 -11 -9 -7] [15 13 11 9 7]
Note:
- When passing negative integers in the
start
and thestop
value innumpy.arange()
, they are treated the same as positive integers. - Passing a negative integer as
step
size creates an array in descending order.
Key Differences Between arange and linspace
Both np.arange()
and np.linspace()
are NumPy functions used to generate numerical sequences, but they have some differences in their behavior.
arange()
generates a sequence of values fromstart
tostop
with a givenstep
size whereaslinspace
generates a sequence ofnum
evenly spaced values fromstart
tostop
.arange()
excludesstop
value whereaslinspace
includesstop
value unless specified otherwise byendpoint = False
Let us look at an example.
import numpy as np
# elements between 10 and 40 with stepsize 4
array1 = np.arange(10, 50 ,4)
# generate 4 elements between 10 and 40
array2 = np.linspace(10, 50 ,4)
print('Using arange:',array1) # doesn't include 50
print('Using linspace:',array2) # includes 50
Output
Using arange: [10 14 18 22 26 30 34 38 42 46] Using linspace: [10. 23.33333333 36.66666667 50. ]